Object detection is particularly important in robotic applications that require interaction with the environment. Although 2D object detection methods obtain accurate results, these are not enough to provide a complete ...

Cardiac magnetic resonance imaging has been proven to be a great aid tool in clinical diagnosis. Computational models arising from these images have been developed for many years by engineers, radiologists and clinicians. ...

Convolutional neural networks (CNN) are powerful tools for learning representations from im-ages. They are being used in a large range of applications, being the state-of-the art in manycomputer vision tasks. In this work, ...

Convolutional Neural Networks (CNNs) is a technology that is evolving very quickly. The CNNs are used in image recognition to improve the computer vision systems in image classification, object detection and segmentation ...

Convolutional Neural Networks have gained popularity in the recent years due to their performance regarding image analysis, both in classification and segmentation. Especially in the medical field, it is increasingly common ...

[ANGLÈS] The aim of this project has been to create a co-saliency detection algorithm for image pairs based on hierarchical segmentation of those images. As hierarchical segmentation allows multi-scale object representation, ...

Deficiencies in the structure of collagen VI are a common cause of neuromuscular diseases. Such diseases typically require assisted ventilation and result in a severely reduced life expectancy. Collagen VI structural defects ...

Les noves tecnologies estan al nostre abastament i fer-ne ús per millorar el rendiment acadèmic del nostre alumnat, és una feina que hem incorporar a l’entorn escolar. Partint d’aquesta premissa i amb aquest esperit he ...